Python Classes and Objects

Python’s object-oriented programming (OOP) allows you to model real-world entities in code, making programs more organized, reusable and easier to maintain. By grouping related data and behavior into a single unit, classes and objects help you write cleaner, more logical code for everything from small scripts to large applications.

Let’s explore how classes and objects work in Python and see them in action with simple examples.

Class

A class in Python is a user-defined template for creating objects. It bundles data and functions together, making it easier to manage and use them. When we create a new class, we define a new type of object. We can then create multiple instances of this object type.

Creating Class

Classes are created using class keyword. Attributes are variables defined inside class and represent properties of the class. Attributes can be accessed using dot . operator (e.g., MyClass.my_attribute).

# define a class
class Dog:
    sound = "bark"  # class attribute

Object

An object is a specific instance of a class. It holds its own set of data (instance variables) and can invoke methods defined by its class. Multiple objects can be created from same class, each with its own unique attributes.

Let's create an object from Dog class.

class Dog:
    sound = "bark"

dog1 = Dog() # Creating object from class
print(dog1.sound) # Accessing the class

bark

Explanation: sound attribute is a class attribute. It is shared across all instances of Dog class, so can be directly accessed through instance dog1.

Why do we need Classes and Objects

• Supports object-oriented programming using reusable templates (classes) and real-world models (objects).
• Promotes code reusability and modular design with organized methods and attributes.
• Simplifies complex programs by grouping related data and behavior.
• Enables key OOP concepts like inheritance, encapsulation and polymorphism.

Using __init__() Function

In Python, class has __init__() function which automatically initializes object attributes when an object is created. The __init__() method is the constructor in Python.

Let’s see how to create a class with __init__() to set up attributes when an object is made:

class Dog:
    species = "Canine"  # Class attribute

    def __init__(self, name, age):
        self.name = name  # Instance attribute
        self.age = age  # Instance attribute

Explanation:

• class Dog: Defines a class named Dog.
• species: class attribute shared by all instances of class.
• __init__ method: Initializes name and age attributes when a new object is created.

Initiate Object with __init__()

Let’s now create an object using __init__() method and see how it initializes attributes:

class Dog:
    species = "Canine"  # Class attribute

    def __init__(self, name, age):
        self.name = name  # Instance attribute
        self.age = age  # Instance attribute

# Creating an object of the Dog class
dog1 = Dog("Buddy", 3)

print(dog1.name)  
print(dog1.species)  

Buddy
Canine

Explanation:

• Dog("Buddy", 3): Creates an object of Dog class with name as "Buddy" and age as 3.
• dog1.name: Accesses instance attribute name of dog1 object.
• dog1.species: Accesses class attribute species of dog1 object.

Self Parameter

self parameter is a reference to the current instance of class. It allows us to access the attributes and methods of the object.

Let’s see an example of how the self parameter works in accessing attributes and methods:

class Dog:
    def __init__(self, name, age):  
        self.name = name 
        self.age = age

    def bark(self): 
        print(f"{self.name} is barking!")

# Creating an instance of Dog
dog1 = Dog("Buddy", 3)
dog1.bark() 

Buddy is barking!

Explanation:

• Inside bark(), self.name accesses specific dog's name and prints it.
• When we call dog1.bark(), Python automatically passes dog1 as self, allowing access to its attributes.

__str__() Method

__str__ method in Python allows us to define a custom string representation of an object. By default, when we print an object or convert it to a string using str(), Python uses the default implementation, which returns a string like <__main__.ClassName object at 0x00000123>.

Let’s look at an example of using __str__() method to provide a readable string output for an object:

class Dog:
    def __init__(self, name, age):
        self.name = name
        self.age = age

    def __str__(self):
        return f"{self.name} is {self.age} years old."
dog1 = Dog("Buddy", 3)
dog2 = Dog("Charlie", 5)

print(dog1)  
print(dog2)  

Explanation:

• __str__ Implementation: Defined as a method in Dog class. Uses self parameter to access instance's attributes (name and age).
• Readable Output: When print(dog1) is called, Python automatically uses __str__ method to get a string representation of object. Without __str__, calling print(dog1) would produce something like <__main__.Dog object at 0x00000123>.

Class and Instance Variables in Python

In Python, variables defined in a class can be either class variables or instance variables and understanding distinction between them is crucial for object-oriented programming.

Class Variables

These are variables that are shared across all instances of a class. It is defined at class level, outside any methods. All objects of class share same value for a class variable unless explicitly overridden in an object.

Instance Variables

Variables that are unique to each instance (object) of a class. These are defined within __init__() method or other instance methods. Each object maintains its own copy of instance variables, independent of other objects.

Example:

This code shows how class variables are shared across all objects, while instance variables are unique to each object.

class Dog:
    # Class variable
    species = "Canine"

    def __init__(self, name, age):
        # Instance variables
        self.name = name
        self.age = age

# Create objects
dog1 = Dog("Buddy", 3)
dog2 = Dog("Charlie", 5)

# Access class and instance variables
print(dog1.species)  # (Class variable)
print(dog1.name)     # (Instance variable)
print(dog2.name)     # (Instance variable)

# Modify instance variables
dog1.name = "Max"
print(dog1.name)     # (Updated instance variable)

# Modify class variable
Dog.species = "Feline"
print(dog1.species)  # (Updated class variable)
print(dog2.species)  

Explanation:

• Class Variable (species): Shared by all instances of class. Changing Dog.species affects all objects, as it's a property of class itself.
• Instance Variables (name, age): Defined in __init__() method. Unique to each instance (e.g., dog1.name and dog2.name are different).
• Accessing Variables: Class variables can be accessed via class name (Dog.species) or an object (dog1.species). Instance variables are accessed via object (dog1.name).
• Updating Variables: Changing Dog.species affects all instances. Changing dog1.name only affects dog1 and does not impact dog2.

Additional Important Concepts in Python Classes and Objects

1. Getter and Setter Methods

Getter and Setter methods provide controlled access to an object's attributes. In Python, these methods are used to retrieve(getter) or modify(setter) values of private attributes, allowing for data encapsulation.

Python doesn't have explicit get and set methods like other languages, but it supports this functionality using property decorators.

• Getter: Used to access value of an attribute.
• Setter: Used to modify value of an attribute.

Let’s see an example of implementing getter and setter methods using @property decorators:

class Dog:
    def __init__(self, name, age):
        self._name = name  # Conventionally private variable
        self._age = age  # Conventionally private variable

    @property
    def name(self):
        return self._name  # Getter

    @name.setter
    def name(self, value):
        self._name = value  # Setter

    @property
    def age(self):
        return self._age  # Getter

    @age.setter
    def age(self, value):
        if value < 0:
            print("Age cannot be negative!")
        else:
            self._age = value  # Setter

Explanation:

• __init__: Initializes private attributes _name and _age.
• @property name: Returns _name value.
• @name.setter: Updates _name.
• @property age: Returns _age value.
• @age.setter: Updates _age if it’s not negative.

2. Method Overriding

Method overriding occurs when a subclass provides a specific implementation of a method that is already defined in its superclass. This allows subclasses to modify or extend behavior of inherited methods.

Let’s look at an example of method overriding, where a subclass changes the behavior of an inherited method:

class Animal:
    def sound(self):
        print("Some sound")

class Dog(Animal):
    def sound(self):  # Method overriding
        print("Woof")

dog = Dog()
dog.sound()  

Woof

Explanation:

• Animal class: Defines a sound() method.
• Dog subclass: Overrides sound() to give a new implementation.
• dog.sound(): Calls overridden method, printing "Woof".

3. Static Methods and Class Methods

Static methods and class methods are bound to the class, not instances of the class.

• Static Method: A method that does not require access to instance or class. It’s defined using @staticmethod decorator.
• Class Method: A method that receives the class as its first argument (cls). It’s defined using @classmethod decorator.

Let’s see how to define and use @staticmethod and @classmethod in Python:

class Dog:
    @staticmethod
    def info():
        print("Dogs are loyal animals.")

    @classmethod
    def count(cls):
        print("There are many dogs of class", cls)

dog = Dog()
dog.info()  # Static method call
dog.count()  # Class method call

Dogs are loyal animals.
There are many dogs of class <class '__main__.Dog'>

Explanation:

• @staticmethod info(): No access to instance or class; prints a general message.
• @classmethod count(cls): Receives the class as cls and prints a message including the class.
• dog.info(): Calls static method.
• dog.count(): Calls class method.

4. Abstract Classes and Interfaces

Abstract classes provide a template for other classes. These classes can't be instantiated directly. They contain abstract methods, which are methods that must be implemented by subclasses.

Abstract classes are defined using abc module in Python. Let’s see an example of using an abstract class to define a required method for subclasses:

from abc import ABC, abstractmethod
class Animal(ABC):
    @abstractmethod
    def sound(self):
        pass

class Dog(Animal):
    def sound(self):
        print("Woof")

dog = Dog()
dog.sound()  

Woof

Explanation:

• from abc import ABC, abstractmethod: Imports tools for creating abstract classes.
• class Animal(ABC): Defines an abstract base class.
• @abstractmethod sound(): Declares a method that must be implemented by subclasses.
• class Dog(Animal): Subclass that implements sound().
• dog.sound(): Calls implemented method, printing "Woof".

5. Class Variables vs. Instance Variables

• Class Variables are shared by all instances of a class. They are defined inside the class but outside any methods.
• Instance Variables are unique to each instance and are defined in __init__() method.

Let’s see difference between a class variable and an instance variable in Python:

class Dog:
    species = "Canine"  # Class variable
    
    def __init__(self, name, age):
        self.name = name  # Instance variable
        self.age = age  # Instance variable

dog1 = Dog("Buddy", 3)
dog2 = Dog("Lucy", 2)

print(dog1.species)  # Accessing class variable
print(dog2.name)  # Accessing instance variable

Canine
Lucy

Explanation:

• species = "Canine": Class variable shared by all Dog objects.
• self.name, self.age: Instance variables unique to each object.
• dog1 = Dog(...) / dog2 = Dog(...): Creates two instances with different names and ages.
• dog1.species: Accesses the class variable.
• dog2.name: Accesses an instance variable.

Python Classes and Objects

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